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Detection of vehicles in shadow areas
Signal and Image Centre, Dept. of Electrical Engineering (SIC-RMA), Brussels, Belgium.
FOI Swedish Defence Research Agency, Linköping, Sweden.
Dept. of Mathematics, Royal Military Academy, Brussels, Belgium.
FOI Swedish Defence Research Agency, Linköping, Sweden.ORCID iD: 0000-0002-6763-5487
2011 (English)In: 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), IEEE , 2011, 1-4 p.Conference paper (Refereed)
Abstract [en]

This paper presents a new method to automatically detect occluded vehicle in semi or deep shadow areas using combined very high resolution (VHR) 3D LIDAR and hyperspectral data. The proposed shape/spectral integration (SSI) decision fusion algorithm was shown to outperform the spectral based anomaly algorithm mainly in deep shadow areas. The fusion of LIDAR DSM data with spectral data is useful in the detection of vehicles in semi and deep shadow areas. The utility of shape information was shown to be a way to enhance spectral target detection in complex urban scene.

Place, publisher, year, edition, pages
IEEE , 2011. 1-4 p.
Series
, Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, ISSN 2158-6268
Keyword [en]
Target detection, 3D LIDAR, hyperspectral, fusion, anomaly detection
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-120509DOI: 10.1109/WHISPERS.2011.6080929ISBN: 978-1-4577-2202-8OAI: oai:DiVA.org:liu-120509DiVA: diva2:845464
Conference
IEEE 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Lisbon, Portugal, 6-9 June 2011
Available from: 2015-08-12 Created: 2015-08-12 Last updated: 2015-09-22Bibliographically approved

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Ahlberg, Jörgen
Computer Vision and Robotics (Autonomous Systems)

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ReferencesLink to record
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